Myoelectric pattern recognition using dynamic motions with limb position changes

2016 ◽  
Author(s):  
Sungtae Shin ◽  
Reza Tafreshi ◽  
Reza Langari
Keyword(s):  
Pattern Recognition ◽  
Limb Position

scholarly journals An Adaptive Multi-Modal Control Strategy to Attenuate the Limb Position Effect in Myoelectric Pattern Recognition

Sensors ◽  
2021 ◽  
Vol 21 (21) ◽  
pp. 7404
Author(s):  
Veronika Spieker ◽  
Amartya Ganguly ◽  
Sami Haddadin ◽  
Cristina Piazza
Keyword(s):  
Pattern Recognition ◽  
Position Effect ◽  
Adaptive Method ◽  
Completion Rate ◽  
Hand Motion ◽  
Limb Position ◽  
Upper Limb Prostheses ◽  
New Information ◽  
Classical Pattern ◽  
External Loads

Over the last few decades, pattern recognition algorithms have shown promising results in the field of upper limb prostheses myoelectric control and are now gradually being incorporated in commercial devices. A widely used approach is based on a classifier which assigns a specific input value to a selected hand motion. While this method guarantees good performance and robustness within each class, it still shows limitations in adapting to different conditions encountered in real-world applications, such as changes in limb position or external loads. This paper proposes an adaptive method based on a pattern recognition classifier that takes advantage of an augmented dataset—i.e., representing variations in limb position or external loads—to selectively adapt to underrepresented variations. The proposed method was evaluated using a series of target achievement control tests with ten able-bodied volunteers. Results indicated a higher median completion rate >3.33% for the adapted algorithm compared to a classical pattern recognition classifier used as a baseline model. Subject-specific performance showed the potential for improved control after adaptation and a ≤13% completion rate; and in many instances, the adapted points were able to provide new information within classes. These preliminary results show the potential of the proposed method and encourage further development.

Resolving the Limb Position Effect in Myoelectric Pattern Recognition

2011 ◽  
Vol 19 (6) ◽  
pp. 644-651 ◽  
Author(s):  
A. Fougner ◽  
E. Scheme ◽  
A. D. C. Chan ◽  
K. Englehart ◽  
Ø. Stavdahl
Keyword(s):  
Pattern Recognition ◽  
Position Effect ◽  
Limb Position

scholarly journals Towards limb position invariant myoelectric pattern recognition using time-dependent spectral features

2014 ◽  
Vol 55 ◽  
pp. 42-58 ◽  
Author(s):  
Rami N. Khushaba ◽  
Maen Takruri ◽  
Jaime Valls Miro ◽  
Sarath Kodagoda
Keyword(s):  
Pattern Recognition ◽  
Time Dependent ◽  
Spectral Features ◽  
Limb Position

scholarly journals Limb Position Tolerant Pattern Recognition for Myoelectric Prosthesis Control with Adaptive Sparse Representations From Extreme Learning

2018 ◽  
Vol 65 (4) ◽  
pp. 770-778 ◽  
Author(s):  
Joseph L. Betthauser ◽  
Christopher L. Hunt ◽  
Luke E. Osborn ◽  
Matthew R. Masters ◽  
Gyorgy Levay ◽  
...  
Keyword(s):  
Pattern Recognition ◽  
Sparse Representations ◽  
Myoelectric Prosthesis ◽  
Limb Position ◽  
Prosthesis Control

scholarly journals Multi-Position Training Improves Robustness of Pattern Recognition and Reduces Limb-Position Effect in Prosthetic Control

2017 ◽  
Vol 29 (2) ◽  
pp. 54-62 ◽  
Author(s):  
Robert J. Beaulieu ◽  
Matthew R. Masters ◽  
Joseph Betthauser ◽  
Ryan J. Smith ◽  
Rahul Kaliki ◽  
...  
Keyword(s):  
Pattern Recognition ◽  
Position Effect ◽  
Prosthetic Control ◽  
Limb Position
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